segMGarch (version 1.3)

pc_Sigma: Method to simulate correlated variables with change-points

Description

An S4 method that takes a simMGarch object and outputs simulated correlated time series with a piecewise constant covariance matrix. The correlations are generated as \(\sigma_{i, i'} = \rho^{|i-i'|}\) with \(\rho\) taking values from \((-1,1)\). The exact variables that will contain a change-point are randomly selected and controlled by r in the simMGarch object.

Usage

pc_Sigma(object)
# S4 method for simMGarch
pc_Sigma(object)

Arguments

object

A simMGarch object.

References

Cho, Haeran, and Karolos Korkas. "High-dimensional GARCH process segmentation with an application to Value-at-Risk." arXiv preprint arXiv:1706.01155 (2017).

Examples

cp=500
n=2000
pw.CCC.obj <- new("simMGarch")
pw.CCC.obj@changepoints=cp
pw.CCC.obj@n=n
pc_Sigma.obj <- pc_Sigma(pw.CCC.obj)
par(mfrow=c(1,2))
#requires corrplot library
#correlation matrix before the changepoint
#corrplot::corrplot.mixed(cor(pc_Sigma.obj@cor_errors[1:cp,]), order="hclust", tl.col="black")
#correlation matrix after the changepoint
#corrplot::corrplot.mixed(cor(pc_Sigma.obj@cor_errors[(cp+1):n,]), order="hclust", tl.col="black")